9 October 2017

Fieldscapes 1.4 released




Fieldscapes v1.4 is now out and available for free download and had some good heavy user testing at Malvern recently with Year 7s from across the county. The main new features in v1.3 and v1.4 are:


  • The start of support for NPC characters through an NPC widget. You can now add an NPC avatar as a prop and have it TP from location to location and activate specific animations - eg "sit". Later releases will allow the NPC to glide or walk between locations. We are also close to releasing a "chatbot" widget to hook an NPC up to an external chatbot system so that you can really start to create virtual characters.
  • General improvements to the UI when in VR mode - users found that the "virtual iPAD" just got in the way so we're now putting the UI directly into the scene. We'll make steady improvements to the usability of the VR experience in future releases
  • Added a new Avatar command to change clothes. This only changes between preset outfits but is good if a character needs to change into special kit for a task - for instance our nursing avatars putting on gloves and aprons (see below)
  • Multiple choice questions are now randomised - makes the student think if they repeat the lesson!
  • Increased the inventory limit from 3 to 5 in the editor - so you can bring in props from more inventories for your scene
  • Increased the word count for multiple-choice panels and default popup panel

Various bug fixes were also made and you can see a full list at http://live.fieldscapesvr.com/Home/Download




v1.4 is already available for PC and Mac. The Android version of v1.4 is just under final testing, and we're also still progressing the iOS version of Fieldscapes through the App Store acceptance process.

Remember: We have an ongoing survey for new Fieldscapes features, please take 2-3 minutes to fill it out at: https://www.surveymonkey.co.uk/r/88YL39B

4 October 2017

Fieldscapes at the Malvern Festival of Innovation

Oculus Rift on the Moon

For the second year in a row we ran a set of workshops at the Malvern Festival of Innovation playing host to a succession of groups of 20-30 students (mostly year 7s) from around Worcestershire and giving them a 1 hour introduction to immersive learning. We set up four stands in order to show the range of experiences and lessons that can be created, and the different ways in which they can be delivered. We had:


  • One laptop running the Solar System lesson
  • One laptop running the Apollo Educate lesson
  • One laptop running the Introduction to Carding Mill (which several groups knew from Fieldtrips)
  • A couple of Google Cardboards, one with the Photosphere tour of Carding Mill and one the Apollo Explore lesson
  • Oculus Rift running Apollo Explore
Playing tag on the Moon!


Students were split into groups of about 5 and had 10 minutes on each "stand" - so everyone got to try all the kit.

Looking at the Waterspout Waterfall in a (plastic) Google Cardboard


Student feedback from comments and feedback forms included:
  • "I wish I could spend all afternoon here"
  • "Can I come back later?"
  • "It was really cool"
  • "It was fun to do"
  • "It was memorable"
  • "The realness of it"
  • "I liked the fact that we were not there but we could see everything"
  • "It was like it was real"
  • "It was educating and fun"
Exploring the Moon and Apollo on Google Cardboard


When talking to the teacher we were keen to highlight that:
  • They didn't have to buy any new hardware, like expensive VR headsets, as they can run lessons in 2D/3D mode on existing computers, or in VR on Google Cardboard (one teacher loaded the app onto his phone as we spoke)
  • They could create their own lessons, share them, and use (and customise) those producted by other users
  • With our licencing model they only started paying once they started using it in class, so they could explore and test for free until they were confident in the system and lessons and were ready to use it in class.
Even the teachers got in on the act!


Fieldscapes itself was rock solid on all the devices all day - despite getting a hammering from the kids. What was particularly impressive was when we had the Apollo experiences in multi-user mode so the kids could play tag on the moon - and even using the public wifi at the venue we had no issues with lag and avatar movement was very smooth.



All in all a great day and helped remind us all why we've built Fieldscapes!





2 October 2017

Abi's Back!



Having been off on sabbatical for a few years whilst we rebuilt the web sites Abi, our virtual assistant is back up. We think she forgot a fair amount whilst she was backpacking around the world, but we'll slowly bring her up to speed, and she's got lots to learn about what with Datascape, Fieldscapes and Trainingscapes. One thing we have given her is the ability to load up web pages - we used to do this on client clients but never got around to doing it on our own!

So if you've got a question about Daden or any of our products just talk to Abi.

This new Abi is built on the Chatscript open source platform that we're using for all our chatbot projects now. She's not the smartest bot we've done, but does give you an idea of the basic sort of functionality and interaction style. When she loads she also provides a page which gives you some idea of her scope and some of the "tricks" we're teaching her.

You can read more about our chatbot work on our dedicated website at www.chatbots.co.uk.

Just get in touch if you'd like to know more about chatbot technology and have a project in mind.

For a quick trip down memory lane here are some of Abi's previous incarnations.

The very first ABI - text and static image in Second Life


Abi as an avatar walking around our old Sim in Second Life



Abi moved onto our website with an art-work avatar


Abi before she went on hols as a photoface avatar


28 September 2017

Fieldscapes and Midwifery Training at Bournemouth University


As you may have seen from our Fieldscapes Twitter stream we've just reached the delivery stage of our first Midwifery Fieldscapes lesson (on Urinalysis) for Bournemouth University's Midwifery training team. We had a number of meetings with the team over the summer and then went away and customised our existing Simple Clinic space into "Daden Community Hospital", and added more generic medical props, and also brought in some BU specific posters. Nash then created the first exercise based on an agreed flowchart/storyboard and now we're just getting to the end of the iterations with the team, stakeholders and students. The final step for us will be to train the BU team on how to use Fieldscapes to continue to maintain and develop the exercise (and create other exercises), before they then start their evaluation with the current student cohort.


Response so far from all involved has been excellent with comments such as:

  • "I had such a cool day at work recently – I got to play with the first of my VR healthcare education environments using Oculus Rift"
  • " I absolutely love this! A brilliant way to learn" - student feedback
  • "So amazing to see my project becoming a reality – I hope the students love this way of bridging the gap between classroom theory and clinical practice"
  • "That was brilliant loved it! can’t wait to do more. Very informative" - student feedback
  • "Delighted that the Oculus Rift dramatically altered the look and feel of the clinical room, and that the handheld Haptic feedback controls added to the experience"


Being Fieldscapes the exercise can be experiences on a PC/Mac or Android device, and in VR on Oculus Rift or Google Cardboard on Android. One of our final tasks is integrating one of the £2-£3 hand controllers for the Cardboard go go along with the c.£15-£20 VR-BOX headsets that BU have (VR doesn't have to be expensive!).



We'll keep you posted as developments and evaluation progress and we're already talking to BU about other exciting way to take the training.


You can read more about the BU view on the project on their blog posts at:






26 September 2017

The Three Big Challenges in AI Development: #2 Generalism and #3 Sentience


Following on from the previous post I now want to look at what happens when we try and move out of the "marketing AI" box and towards that big area of "science fiction" AI to the right of the diagram. Moving in this direction we face two major challenges, #2 and #3 of our overall AI challenges:

Challenge #2: Generalism

Probably the biggest "issue" with current "AI" is that it is very narrow. It's a programme to interpret data, or to drive a car, or to play chess, or to act as a carer, or to draw a picture. But almost any human can make a stab at doing all of those, and with a bit of training or learning can get better at them all. This just isn't the case with modern "AI". If we want to get closer to the SF ideal of AI, and also to make it a lot easier to use AI in the world around us, then what we really need is a "general purpose AI" - or what is commonly called Artificial General Intelligence (AGI). There is a lot of research going into AGI at the moment in academic institutions and elsewhere, but it is really early days. A lot of the ground work is just giving the bot what we would call common-sense - just knowing about categories of things, what they do, how to use them - the sort of stuff a kid picks up before they leave kindergarten. In fact one of the strategies being adopted is to try and build a virtual toddler and get it to learn in the same way that a human toddler does.

Whilst the effort involved in creating an AGI will be immense, the rewards are likely to be even greater - as we'd be able to just ask or tell the AI to do something and it would be able to do it, or ask us how to do it, or go away and ask another bot or research it for itself. In some ways we would cease to need to programme the bot.

Just as a trivial example, but one that is close to our heart. If we're building a training simulation and want to have a bunch of non-player characters filling roles then we have to script each one, or create behaviour models and implement agents to then operate within those behaviours. It takes a lot of effort. With an AGI we'd be able to treat those bots as though they were actors (well extras) - we'd just give them the situation and their motivation, give some general direction, shout "action" and then leave them to get on with it.

Not also that moving to an AGI does not imply ANY linkage to the level of humanness. It is probably perfectly possible to have a fully fledged AGI that only has the bare minimum of humanness in order to communicate with us - think R2D2.

Challenge #3: Sentience

If creating an AGI is probably an order of magnitude greater problem than creating "humanness", then creating "sentience" is probably an order of magnitude greater again. Although there are possibly two extremes of view here:


  • At one end many believe that we will NEVER create artificial sentience. Even the smartest, most human looking AI will essentially be a zombie, there's be "nobody home", no matter much much it appears to show intelligence, emotion or empathy.
  • At the other, some believe that if we create a very human AGI then sentience might almost come with it. In fact just thinking back to the "extras" example above our anthropological instinct almost immediately starts to ask "well what if the extras don't want to do that..."
We also need to be clear about what we (well I) mean when I talk about sentience. This is more than intelligence, and is certainly beyond what almost all (all?) animals show. So it's more than emotion and empathy and intelligence. It's about self-awareness, self-actualisation and having a consistent internal narrative, internal dialogue and self-reflection. It's about being able to think about "me" and who I am, and what I'm doing and why, and then taking actions on that basis - self-determination.

Whilst I'm sure we code a bot that "appears" to do much of that, would that mean we have created sentience - or does sentience have to be an emergent behaviour? We have a tough time pinning down what all this means in humans, so trying to understand what it might mean (and code it, or create the conditions for the AGI to evolve it) is never going to be easy.




So this completes our chart. To move from the "marketing" AI space of automated intelligence to the science-fiction promise of "true" AI, we face three big challenges, each probably an order of magnitude greater than the last:


  • Creating something that presents as 100% human across all the domains of "humanness"
  • Creating an artificial general intelligence that can apply itself to almost any task
  • Creating, or evolving, something that can truly think for itself, have a sense of self, and which shows self-determination and self-actualisation
It'll be an interesting journey!



25 September 2017

The Three Big Challenges in AI Development: #1 Humanness





In a previous blog post we introduced our AI Landscape diagram. In this post I want to look at how it helps us to identify the main challenges in the future development of AI.

On the diagram we’ve already identified how that stuff which is currently called “AI” by marketeers, media and others is generally better thought of as being automated intelligence or “narrow” AI. It is using AI techniques, such as natural language or machine learning, and applying them to a specific problem, but without actually building the sort of full, integrated, AI that we have come to expect from Science Fiction.

To grow the space currently occupied by today’s “AI” we can grow in two directions – moving up the chart to make the entities seem more human, or moving across the chart to make the entities more intelligent.

MORE HUMAN

The “more human”  route represents Challenge 1. It is probably the easiest of the challenges and the chart we showed previously (and repeated below) shows an estimate of the relative maturity of some of the more important technologies involved.



There are two interesting effects related to work in this direction:


  • Uncanny Valley - we're quite happy to deal with cartoons, and we're quite happy to deal with something that seems completely real, but there's a middle ground that we find very spooky. So in some ways the efficacy of developments rise as they get better, then plummet as they hit the valley, and then finally improve again once you cannot tell them for real. So whilst in some ways we've made a lot of progress in some areas over recent years (e.g. visual avatars, text-to-speech) we're now hitting the valley with them and progress may now seem a lot slower. Other elements, like emotion and empathy, we're barely started on, so may take a long time to even reach the valley.
  • Anthropomorphism - People rapidly attribute feelings and intent to even the most inanimate object (toaster, printer). So in some ways a computer needs to do very little in the human direction for us to think of it as far more human than it really is. In some ways this can almost help us cross the valley by letting human interpretation assume the system has crossed the valley even though it's still a lot more basic than is thought.
The upshot is that the next few years will certainly see systems that seem far more human than any around today, even though their fundamental tech is nowhere near being a proper "AI". The question is whether a system could pass the so-called "Gold" Turing Test ( a Skype like conversation with an avatar) without also showing significant progress along the intelligence dimension. Achieving that is probably more about the capability of the chat interface as it seems that CGI and Games will crack the visual and audio elements (although ding them in real-time is still a challenge) - so it really remains the standard Turing challenge. An emotional/empathic version of the Turing Test will probably prove a far harder nut to crack.

We'll discuss the Intelligence dimension in Part 2.





18 September 2017

Automated Intelligence vs Automated Muscle

As previously posted I've long had an issue with the "misuse" of the term AI. I usually replace "AI" with "algorithms inside" and the marketing statement I'm reading still makes complete sense!

Jerry Kaplan speaking on the Today programme last week was using the term "automation" to refer to what a lot of current AI is doing - and actually that fits just as well, and also highlights that this is something more than just simple algorithms, even if it's a long way short of science-fiction AIs and Artificial General Intelligence.

So now I'm happy to go with "automated intelligence" as what modern AI does - it does automate some aspects of a very narrow "intelligence" - and the use of the word automated does suggest that there are some limits to the abilities (which "artificial" doesn't).

And seeing as I was at an AI and Robotics conference last week that also got me to thinking that robotics is in many ways just "automated muscle", giving us a nice dyad with advanced software manifesting itself as automated intelligence (AI), and advanced hardware manifesting as automated muscle (robots).